def store_data(df, blotter=None, kind="BAR"):
"""
Store QTPyLib-compatible csv files in Blotter's MySQL.
TWS/GW data are required for determining futures/options expiration
:Parameters:
df : dict
Tick/Bar data
:Optional:
blotter : str
Store MySQL server used by this Blotter (default is "auto detect")
kind : str
Is this ``BAR`` or ``TICK`` data
"""
# validate columns
valid_cols = validate_columns(df, kind)
if not valid_cols:
raise ValueError('Invalid Column list')
# load blotter settings
blotter_args = load_blotter_args(
blotter, logger=logging.getLogger(__name__))
# blotter not running
if blotter_args is None:
raise Exception("Cannot connect to running Blotter.")
# cannot continue
if blotter_args['dbskip']:
raise Exception("Cannot continue. Blotter running with --dbskip")
# connect to mysql using blotter's settings
dbconn = pymysql.connect(
client_flag=MULTI_STATEMENTS,
host=str(blotter_args['dbhost']),
port=int(blotter_args['dbport']),
user=str(blotter_args['dbuser']),
passwd=str(blotter_args['dbpass']),
db=str(blotter_args['dbname']),
autocommit=True
)
dbcurr = dbconn.cursor()
# loop through symbols and save in db
for symbol in list(df['symbol'].unique()):
data = df[df['symbol'] == symbol]
symbol_id = get_symbol_id(symbol, dbconn, dbcurr)
# prepare columns for insert
data.loc[:, 'timestamp'] = data.index.strftime('%Y-%m-%d %H:%M:%S')
data.loc[:, 'symbol_id'] = symbol_id
# insert row by row to handle greeks
data = data.to_dict(orient="records")
if kind == "BAR":
for _, row in enumerate(data):
mysql_insert_bar(row, symbol_id, dbcurr)
else:
for _, row in enumerate(data):
mysql_insert_tick(row, symbol_id, dbcurr)
try:
dbconn.commit()
except Exception as e:
return False
return True
def store_data(df, blotter=None, kind="BAR"):
"""
Store QTPyLib-compatible csv files in Blotter's MySQL.
TWS/GW data are required for determining futures/options expiration
:Parameters:
df : dict
Tick/Bar data
:Optional:
blotter : str
Store MySQL server used by this Blotter (default is "auto detect")
kind : str
Is this ``BAR`` or ``TICK`` data
"""
# validate columns
valid_cols = validate_columns(df, kind)
if not valid_cols:
raise ValueError('Invalid Column list')
# load blotter settings
blotter_args = load_blotter_args(blotter, logger=logging.getLogger(__name__))
# blotter not running
if blotter_args is None:
raise Exception("Cannot connect to running Blotter.")
return False
# cannot continue
if blotter_args['dbskip']:
raise Exception("Cannot continue. Blotter running with --dbskip")
return False
# connect to mysql using blotter's settings
dbconn = pymysql.connect(
host = str(blotter_args['dbhost']),
port = int(blotter_args['dbport']),
user = str(blotter_args['dbuser']),
passwd = str(blotter_args['dbpass']),
db = str(blotter_args['dbname']),
autocommit = True
)
dbcurr = dbconn.cursor()
# loop through symbols and save in db
for symbol in list(df['symbol'].unique()):
data = df[df['symbol'] == symbol]
symbol_id = get_symbol_id(symbol, dbconn, dbcurr)
# prepare columns for insert
data.loc[:, 'timestamp'] = data.index.strftime('%Y-%m-%d %H:%M:%S')
data.loc[:, 'symbol_id'] = symbol_id
# insert row by row to handle greeks
data = data.to_dict(orient="records")
if kind == "BAR":
for _, row in enumerate(data):
mysql_insert_bar(row, symbol_id, dbcurr)
else:
for _, row in enumerate(data):
mysql_insert_tick(row, symbol_id, dbcurr)
try:
dbconn.commit()
except:
return False
return True